Chemical state estimation for the middle atmosphere by four‐dimensional variational data assimilation: System configuration

Abstract

[1] A novel stratospheric chemical data assimilation system has been developed and applied to Environmental Satellite Michelson Interferometer for Passive Atmospheric Sounding (ENVISAT/MIPAS) data, aiming to combine the sophistication of the four-dimensional variational (4D-var) technique with flow-dependent covariance modeling and also to improve numerical performance. The system is tailored for operational stratospheric chemistry state monitoring. The atmospheric model of the assimilation system includes a state-of-the-art stratospheric chemistry transport module along with its adjoint and the German weather service's global meteorological forecast model, providing meteorological parameters. Both models share the same grid and same advection time step, to ensure dynamic consistency without spatial and temporal interpolation errors. A notable numerical efficiency gain is obtained through an icosahedral grid. As a novel feature in stratospheric variational data assimilation a special focus was placed on an optimal spatial exploitation of satellite data by dynamic formulation of the forecast error covariance matrix, providing potential vorticity controlled anisotropic and inhomogeneous influence radii. In this first part of the study the design and numerical features of the data assimilation system is presented, along with analyses of two case studies and a posteriori validation. Assimilated data include retrievals of O 3 , CH 4 , N 2 O, NO 2 , HNO 3 , and water vapor. The analyses are compared with independent observations provided by Stratospheric Aerosol and Gas Experiment II (SAGE II) and Halogen Occultation Experiment (HALOE) retrievals. It was found that there are marked improvements for both analyses and assimilation based forecasts when compared with control model runs without any data ingestion.

A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 1: Offline forward and adjoint transport models

“…However, there are still only a few studies of its applications in atmospheric chemistry and inversion/assimilation calculations (e.g., Elbern et al, 2010). One prominent feature of the NICAM-TM 4D-Var system is the perfect mass conservation, as described in Sect 2.1.…”

Importance of using ensemble estimated background error covariances for the quality of atmospheric ozone analyses

“…We therefore plan to find a way to estimate this matrix on-line. An interesting approach would be to parametrize the covariance matrix with other physical parameters, as Elbern et al (2010) did for the potential vorticity.…”

“…Since then, except for the recent work of Schwinger and Elbern (2010), evaluation of the BECM for global atmospheric chemistry has not been the object of thorough investigations. Previous work concerning the BECM is mainly focused on its formulation for atmospheric applications (Bannister 2008a(Bannister , 2008b or atmospheric chemistry (Pannekoucke and Massart, 2008;Elbern et al, 2010).…”

On the diffusion equation and its application to isotropic and anisotropic correlation modelling in variational assimilation

“…Weaver and Courtier (2001) (hereafter WC01) described the algorithm in more detail and proposed various extensions to account for more general correlation functions than the quasi-Gaussian of the original Derber and Rosati (1989) algorithm. Correlation models based on explicit diffusion methods have been used in various VDA systems in oceanography (Weaver et al, 2003;Di Lorenzo et al, 2007;Muccino et al, 2008;Daget et al, 2009;Kurapov et al, 2009;Moore et al, 2011), meteorology (Bennett et al 1996), and atmospheric chemistry (Geer et al, 2006;Elbern et al, 2010).…”